The Emergence of Informative Higher Scales in Complex Networks
The connectivity of a network contains information about the relationships between nodes, which can denote interactions, associations, or dependencies. We show that this information can be analyzed by measuring the uncertainty (and certainty) contained in paths along nodes and links in a network. Sp...
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Online Access: | http://dx.doi.org/10.1155/2020/8932526 |
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doaj-63425c5934b14deba7642264f7ee7c1d2020-11-25T02:04:12ZengHindawi-WileyComplexity1076-27871099-05262020-01-01202010.1155/2020/89325268932526The Emergence of Informative Higher Scales in Complex NetworksBrennan Klein0Erik Hoel1Network Science Institute, Northeastern University, Boston, MA 02115, USAAllen Discovery Center, Tufts University, Medford, MA 02155, USAThe connectivity of a network contains information about the relationships between nodes, which can denote interactions, associations, or dependencies. We show that this information can be analyzed by measuring the uncertainty (and certainty) contained in paths along nodes and links in a network. Specifically, we derive from first principles a measure known as effective information and describe its behavior in common network models. Networks with higher effective information contain more information in the relationships between nodes. We show how subgraphs of nodes can be grouped into macronodes, reducing the size of a network while increasing its effective information (a phenomenon known as causal emergence). We find that informative higher scales are common in simulated and real networks across biological, social, informational, and technological domains. These results show that the emergence of higher scales in networks can be directly assessed and that these higher scales offer a way to create certainty out of uncertainty.http://dx.doi.org/10.1155/2020/8932526 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Brennan Klein Erik Hoel |
spellingShingle |
Brennan Klein Erik Hoel The Emergence of Informative Higher Scales in Complex Networks Complexity |
author_facet |
Brennan Klein Erik Hoel |
author_sort |
Brennan Klein |
title |
The Emergence of Informative Higher Scales in Complex Networks |
title_short |
The Emergence of Informative Higher Scales in Complex Networks |
title_full |
The Emergence of Informative Higher Scales in Complex Networks |
title_fullStr |
The Emergence of Informative Higher Scales in Complex Networks |
title_full_unstemmed |
The Emergence of Informative Higher Scales in Complex Networks |
title_sort |
emergence of informative higher scales in complex networks |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2020-01-01 |
description |
The connectivity of a network contains information about the relationships between nodes, which can denote interactions, associations, or dependencies. We show that this information can be analyzed by measuring the uncertainty (and certainty) contained in paths along nodes and links in a network. Specifically, we derive from first principles a measure known as effective information and describe its behavior in common network models. Networks with higher effective information contain more information in the relationships between nodes. We show how subgraphs of nodes can be grouped into macronodes, reducing the size of a network while increasing its effective information (a phenomenon known as causal emergence). We find that informative higher scales are common in simulated and real networks across biological, social, informational, and technological domains. These results show that the emergence of higher scales in networks can be directly assessed and that these higher scales offer a way to create certainty out of uncertainty. |
url |
http://dx.doi.org/10.1155/2020/8932526 |
work_keys_str_mv |
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1715582644288225280 |